Service Level Model, Algorithm, Systems and Methods

ABSTRACT

Systems and methods for modeling staffing service levels in a workplace is disclosed. Such a system can include memory that stores instructions and a processor that executes the instructions to perform operations. The operations can include receiving questionnaire responses to a questionnaire that elicits a perception of staffing service level factors of a plurality of representatives, where the questionnaire responses are provided by one of company representatives, company workforce representatives or a combination thereof. The operations can also include selecting questionnaire responses of the representatives, determining an expected staffing service level, calculating representative questionnaire scores, comparing the representative questionnaire scores to a statistical model, and determining a staffing service level tendency based on comparing the representative questionnaire scores to the statistical model, where the staffing service level tendency indicates a likelihood that a maximum staffing service level will at least meet the expected staffing service level given the current circumstances of the company.

FIELD OF THE INVENTION

The present application generally relates to staffing service levels andmore particularly relates to predicting the maximum service levelsattainable by a provider of contingent labor for a specific company,under the given circumstances.

BACKGROUND

Companies often turn to providers of contingent labor, or temporarystaff, as customers or clients to address workforce needs that occurfrom time to time. Contingent labor can include skilled or unskilledworkers that can address increases in work volume, desires to completeprojects faster or for other reasons. Staffing service level means themeasure of the ability of a contingent workforce provider to deliverstaffing services to a company pursuant to the company's performanceexpectations. The performance of providers of contingent labor is oftenjudged by the companies that engage them based on the ability to obtainand retain qualified contingent workforces for specified periods oftime. The workforce needs of a company, or a customer or client of aprovider of contingent labor, can be based on a variety of factors,including the amount of work to be completed, the amount of time tocomplete the work and any particularized skill sets needed to completethe work. The term, the length of employment, duration of employment orattrition of contingent workforce members, and even full time workforcemembers, however, is not uniform.

SUMMARY

The present application includes systems and methods for predicting themaximum staffing service level attainable by any provider of contingentlabor for that particular company given the company's currentconditions. With the systems and methods disclosed herein, thecontingent workforce provider will be able to identify the areas ofopportunity to modify so that the maximum staffing service levelattainable can be increased or improved.

Various systems and accompanying methods for modeling staffing servicelevels are disclosed. The system may enable a provider of contingentworkforces to collaborate with clients to predict or calculate theclient's maximum attainable level of service from any contingentworkforce provider under the company's current circumstances. The systemcan also determine whether the staffing service level perceptions of thevarious company management levels, temporary workforce, and full-timeworkforce, and any other groups or levels at the company, collectivelythe company's hierarchical levels or groups, meet, exceed, or are belowthe maximum service level attainable at that company under those currentcircumstances. The system can also compare the perceptions of eachhierarchical group to identify variances between the groups. A value orscore can also be calculated for these perceptions. The value or scorecan be used by a statistical model to predict or calculate tendencies.Further, the value or score can be compared to a plurality ofcorresponding company values or scores.

The system can use questionnaires that elicit a perception of staffingservice level factors according to the perspective of various companyrepresentatives. These company representatives can be at differenthierarchical levels within a company, including executives, hiringmanagers, line managers, full-time employees, and temporary employees.The responses to the questionnaires can be scored and compared to boththe statistical model and corresponding company values. The statisticalmodel produces or calculates a numeric value representative of the totalcompany, which can be a score, and the model also produces or calculatesa score for each hierarchical group. The score is a numericrepresentation of the expected staffing service level given thecompany's current conditions. The system can also retrieve an average ofthe real world staffing metrics and deliverables from a plurality ofcompanies with corresponding scores to provide what typical maximumstaffing service levels the company can expect. Which companies arelike, similar or corresponding companies can be determined by aselection of matching companies based on a plurality of secondary datavariables, such as demographics, industry, geographic region, companysize and company function. Other relevant secondary data can also becompared to identify corresponding companies. The system can also map toa database containing a multitude of scores and client staffing metricdata.

Staffing service level tendencies as compared to the statistical modelcan be obtained for each hierarchical group of scores and plausibletendencies can be determined from comparisons of these scores to themodel. The hierarchical group of scores is a weighted average of allresponses from each hierarchical level at the company. In addition, theoverall staffing service level tendency as compared to the statisticalmodel can be obtained for the overall company score and plausibletendencies can be determined from comparisons of this score to themodel. The overall company score is a weighted average of all companyresponses.

By comparing the company's overall score to scores of correspondingcompanies, based on secondary data variables, a company's maximumstaffing service level can be determined. This comparison can alsoinclude many secondary data variables, such as demographics, industry,geographic region, company size and company function, that can be usedto broaden or limit the scope of the comparison. For example, an overallcompany score can be compared to other companies within the same cityand the same industry that have a similar size. As an alternativeexample, an overall company score can be compared to other companieswithin the same industry across multiple cities that have the same citypopulation size.

Further, the systems, methods and models can evolve over time as thequestionnaire scores are saved and the model is recalculated over time.The responses to these saved questionnaires can also determine therelevancy of the various questions as they pertain to the model. Therelevancy can then influence the weighting of each questionnaireresponse. This evolution of the model provides for a greater alignmentbetween the model and the predicted or calculated tendencies.

In one embodiment, a system for modeling staffing service levels isprovided. The system can include memory that stores instructions and aprocessor that executes the instructions to perform operations. Theoperations can include receiving an expected staffing service level,given the company's current conditions from questionnaire responses to aquestionnaire that elicits a perception of staffing service levelfactors of a company representative, where the questionnaire responsesare provided by the company representative. Additionally, the operationscan also include selecting questionnaire responses of the companyrepresentative, calculating a company representative questionnairescore, and comparing the company representative questionnaire score to astatistical model. Further, the operations can include determining astaffing service level tendency based on comparing the companyrepresentative questionnaire score to the statistical model, where thestaffing service level tendency indicates the likelihood that a renderedservice level will at least meet the expected staffing service level.Additionally, the company representative can be an executive level orhiring manager/supervisor employee.

In another embodiment, the operations can include receivingquestionnaire responses to the questionnaire that elicits a perceptionof staffing service level factors of a plurality of companyrepresentatives, where the company representatives can be grouped intohierarchical levels or roles within the company. Further, the operationscan include selecting a hierarchical grouping of questionnaire responsesof the company representatives, calculating a hierarchical groupquestionnaire score, and comparing the hierarchical group questionnairescore to a statistical model. They can also include determining astaffing service level tendency based on comparing the hierarchicalgroup questionnaire score to the statistical model, where the staffingservice level tendency indicates the likelihood that a rendered servicelevel will at least meet the expected staffing service level.

In another arrangement, the operations can also include comparing thehierarchical group questionnaire scores to the questionnaire scores ofthe one or more other company hierarchical groups. Further, thiscomparison can include performing a gap analysis of the scores todetermine the variance of expected staffing service levels between thehierarchical groups. This analysis can identify areas of opportunity tobring the expected staffing service level of the various hierarchicalgroups into closer alignment.

Still further, the operations can include receiving questionnaireresponses to the questionnaire that elicits a perception of staffingservice level factors of contingent or full-time company workforcerepresentatives, where the questionnaire responses are provided by acontingent or full-time company workforce representative. The operationscan also include selecting questionnaire responses of the contingent orfull-time company workforce representatives, calculating a contingent orfull-time company workforce representative questionnaire score,comparing the contingent or full-time company workforce representativequestionnaire scores to executive, hiring manager/supervisory or othercompany representative scores, and determining a tendency based oncomparing the contingent or full-time company workforce representativescores to the executive, hiring manager/supervisory or other companyrepresentative scores. Additionally, a gap analysis can be performed onthe variances between the scores to determine opportunities to bring theexpected staffing service level between the contingent or full-timecompany workforce representatives and the executive, hiringmanager/supervisory or other company representatives into closeralignment.

In yet another arrangement, the operations can include updating thecorresponding company scores with the questionnaire responses providedby the overall company and recalculating a statistical model based onthe updated corresponding company scores. Further, they can includeupdating the corresponding company scores with the questionnaireresponses received from the company representatives and calculatingmaximum staffing service level averages associated with a range ofcorresponding company scores. Also, they can include identifying outcomedeterminative factors from the staffing service level factors, providingsuggested changes, in response to identifying outcome determinativefactors, to increase the chance that the rendered service level will atleast meet the expected staffing service level.

In another embodiment, a method for modeling staffing service levels isprovided. The method can include receiving an expected staffing servicelevel from questionnaire responses to a questionnaire that elicits aperception of staffing service level factors of a multitude of companyrepresentatives, where the questionnaire responses are provided by thecompany representatives. The method can also include selectingquestionnaire responses of the company representatives, calculating anoverall company questionnaire score, comparing the overall companyquestionnaire score to a statistical model, and determining a staffingservice level tendency based on comparing the overall companyquestionnaire score to the statistical model, where the expectedstaffing service level tendency indicates a likelihood that a renderedservice level will meet or be more or less likely to exceed the averagemaximum staffing service level.

In another embodiment, a computer-readable device is provided. Thecomputer-readable device can include instructions, which when executedby a processor, cause the processor to perform operations. Theoperations can include receiving an expected staffing service level fromquestionnaire responses to a questionnaire that elicits a perception ofstaffing service level factors of a multitude of companyrepresentatives, where the questionnaire responses are provided by thecompany representatives. The operations can also include selectingquestionnaire responses of the company representatives, calculating anoverall company questionnaire score, comparing the overall companyquestionnaire score to a statistical model, and determining a staffingservice level tendency based on comparing the overall companyquestionnaire score to the statistical model, where the expectedstaffing service level tendency indicates a likelihood that a renderedservice level will meet or be more or less likely to exceed the averagemaximum staffing service level.

These and other features of the systems and methods for modelingstaffing service levels are described in the following detaileddescription, drawings, and appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration featuring a view of a system formodeling staffing service levels according to an embodiment of thepresent disclosure.

FIG. 2 is an exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 3 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 4 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 5 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 6 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 7 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 8 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 9 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 10 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 11 is another exemplary questionnaire that elicits a perception ofstaffing service level factors of a company representative according tothe present disclosure.

FIG. 12 is a flow diagram illustrating a sample method for modelingstaffing service levels according to the present disclosure.

FIG. 13 is a flow diagram illustrating a sample method for addressingstaffing service levels according to the present disclosure.

FIG. 14 is a diagrammatic representation of a machine in the form of acomputer system within which a set of instructions, when executed, maycause the machine to perform any one or more of the methodologiesdiscussed herein.

DETAILED DESCRIPTION

A system 100 for modeling staffing service levels that are desired by acompany and that can be attained by a provider of contingent workforceis disclosed in the present disclosure. Referring to the drawings and inparticular to FIG. 1, the system 100 may enable a modeling server 110 toreceive and process questionnaire responses from one or more companyrepresentatives utilizing one or more devices 120, 130 to inputquestionnaire responses.

The server or device 110 may include one or more electronic processors112, which may be configured to handle any necessary processing forcarrying out any and all of various operative functions of the system100. The electronic processors 112 may be software, hardware, or acombination of hardware and software. Additionally, the server 110 mayalso include a memory 114, which may be configured to store instructionsthat the electronics processors 112 may execute to perform various theoperations of the system 100. For example, the server 110 may receivequestionnaire response data from the company representative utilizinghandheld device 120 and perform the necessary operations to comparecompany representative questionnaire scores to a statistical model,determine staffing service level tendencies, compare companyrepresentative questionnaire scores to corresponding company scores andother operations and functions discussed herein.

In one embodiment, multiple servers or devices 110 may be utilized toprocess the functions of the system 100. The server 110 or the device110, or both, may utilize the database 140 for storing a plurality ofstored previous company responses, previous calculations andcorresponding company staffing service levels, along with any other datathat the devices in the system 100 may utilize in processing. In anembodiment, multiple databases 140 may be utilized to store data in thesystem 100. Notably, the system 100 may utilize a combination ofsoftware and hardware to perform the operative functions of the system100 disclosed herein. Additionally, although FIG. 1 illustrates specificexample configurations of the various components of the system 100, thesystem 100 may include any configuration of the components, which mayinclude using a greater or lesser number of the components.

Furthermore, the communications network 135 may be any suitable networkthat may be utilized to allow the various components of the system 100to communicate with one another. For instance, the communicationsnetwork 135 may be a wireless network, an ethernet network, a satellitenetwork, a broadband network, a cellular network, a private network, acable network, the Internet, or any combination thereof.

The system and methods disclosed herein relate to modeling staffingservice levels that will likely be rendered under a set of givencircumstances. The modeled staffing service level, which is the maximumstaffing service level that can be achieved by a contingent workforcegiven the company's current circumstances, may differ from a company'sor client's expected staffing service level. The maximum staffingservice level may differ for any particular client, and there can becompany or client specific criteria or criterions used to determinewhether a contingent workforce provider met the client's staffing needs.Thus, the maximum staffing service level can be the ability of aprovider of contingent workforce, or a staffing company, to meet certaincriteria. Accordingly, the maximum staffing service level may includethe ability of the contingent workforce provider to deliver or obtainthe client's desired number of contingent employees for a particularassignment or project. The maximum staffing service level may alsoinclude the ability of the contingent workforce provider to deliver orobtain the client's desired contingent employees with appropriate skillor experience levels for a particular assignment or project. The maximumstaffing service level may also include the ability of the contingentworkforce provider to deliver or obtain the contingent employeesconsistent with a timeline established by the client. The maximumstaffing service level may also include the ability of the contingentworkforce provider to maintain the contingent employees for the durationof a particular assignment. The maximum staffing service level may alsoinclude the ability of the contingent workforce provider to deliver anycombination of the above.

The system and methods disclosed herein include questionnaires andresponses to the questionnaires from one or more companyrepresentatives. The questionnaires can include a variety of questionsthat relate to, and that do not relate to, a company representative'sperception of staffing service level factors. One or more combinationsof the staffing service level factors can be determinative of whetherthe contingent labor provider will be able to meet or exceed theclient's expected staffing service level. The staffing service levelfactors may include employee work conditions, staffing level needs,employee satisfaction and other issues. Available answers to theindividual questions within the questionnaire can include a numericalrating scale, such as a Likert-type scale. Answers to the individualquestions within the questionnaire can also be numerical responses toquestions, such as the number of average temporary employees or theaverage staffing service level. Further, answers to the individualquestions within the questionnaire can include a ranking of order ofimportance of two or more pre-defined answers. Still further, answers tothe individual questions within the questionnaire can include theselection of a single most accurate non-numerical answer from a list ofpossible non-numerical answers.

FIGS. 2-5 are exemplary questions and/or statements of questionnairesthat are designed to illicit a perception of staffing service levelfactors of a company representative. The questions, however, are notlimited to being designed to illicit a perception of staffing servicelevel factors. For example, some questions can be included to determinea company representative's, or a client's, service level expectations.Other questions can be included to determine current demographic data.Other questions not related to staffing service levels can also beincluded.

As shown in FIGS. 2-4, the questions can include statements regardingstaffing service level factors. The staffing service level factors mayinclude topics related to work conditions, including an employer'sperception of partnering with a contingent workforce provider, theeffect of a deficit in the desired number of temporary employees, thebenefits provided by the employer, employee satisfaction and otherfactors.

The available answers to the statements in FIGS. 2-4 include a rankingfrom 1-10 to indicate the company representative's agreement ordisagreement with the statement. The company representative's responsecan include the degree to which the company representative agrees or thedegree to which the company representative disagrees with the statement.For example, if the company representative strongly disagrees with thestatement, the company representative can select the first response witha value of one. On the other hand, if the company representativestrongly agrees with the statement, the company representative canselect the response with a value of 10. The company representative canalso select “Don't Know Answer” to indicate that the companyrepresentative does not know the answer to the question or statement. Inone embodiment, the exemplary questionnaire can be implemented via a webpage with appropriate toggle or radio buttons or the like for thecompany representative to select their answers to the individualquestions. The answers can then be received by, for example, awebserver.

FIG. 5 includes additional statements regarding a category of staffingservice level factors related to turnover propensity. The turnoverpropensity statements can provide insight into the likelihood that oneor more temporary employees will not complete the intended oranticipated duration of temporary employment. The available answers tothe statements in FIG. 5 include a ranking from 1-10 to indicate thecompany representative's agreement or disagreement with the statement.The company representative's response can include the degree to whichthe company representative agrees or the degree to which the companyrepresentative disagrees with the statement. Other exemplary questionsor statements can include the following: temporary employees are treatedwith the same respect as full-time employees; employees would say weprovide an excellent physical work environment; employees would say theylove working at our company; there are opportunities for a temporaryemployee to transition to a full-time position; employees would describeour company policies as very fair; our corporate work culture brings outthe best in all of our employees; the greatest demand skill set ishighly sought in our geographic region; temporary employees are fullyequipped with the right training and materials to perform their jobwell; temporary employees feel genuinely cared for; there areopportunities for temporary employees to receive individual recognitionfor excellent performance; temporary employees receive feedback to helpimprove their performance; our current temporary turnover level isreasonable and acceptable; our temporary employee turnover rate is lowerthan similar companies in the area; and pay rates for temporaryemployees similar to similar companies. Any combination of suchquestions may be utilized.

In one embodiment, the exemplary questionnaire can be implemented via aweb page with appropriate toggle or radio buttons or the like for theemployer representative to select their answers to the individualquestions. The answers can then be received by, for example, awebserver.

FIG. 6 illustrates additional exemplary questions for use in aquestionnaire. The questions of FIG. 6 and its format for providing ananswer are designed to elicit a numerical response to be provided by auser. For instance, the questions elicit the number of average temporaryemployees from an employer representative and the number of days of thetypical length of a temporary assignment. Again, the exemplaryquestionnaire can be implemented via a web page with appropriate fieldsor the like for the employer representative to input their answers tothe individual questions. The answers can then be received by, forexample, a webserver.

FIG. 7 illustrates a different embodiment of an additional exemplaryquestion for use in a questionnaire. The questions of FIG. 7 include alist of possible answers that reflect an company representative'sperception of average length of temporary employee employment andwhether such employment is continuous or intermittent. Other questionswith pre-populated answers can also be included. The exemplaryquestionnaire can be implemented via a web page with appropriate fieldsor the like for the company representative to input their answer(s) tothe individual question(s). The answers can then be received by, forexample, a webserver.

FIG. 8 illustrates yet another embodiment of an additional exemplaryquestion for use in a questionnaire. The question of FIG. 8 includes a“yes” or “no” answer for selection by the company representative astheir answer to the question. Other questions with “yes” or “no”answers, or “true” or “false” answers can also be provided. Theexemplary questionnaire can be implemented via a web page withappropriate fields or the like for the employer representative to inputtheir answer(s) to the individual question(s). The answers can then bereceived by, for example, a webserver.

FIG. 9 illustrates yet another embodiment of an additional exemplaryquestion for use in a questionnaire. The question of FIG. 9 is formattedto elicit a numerical value for the percentage of employees working at aparticular employer during a particular shift. For instance, theemployer representative can provide answers of 5%, 25%, 0% and 30%,respectively, for the first, second, third shift and total. Theexemplary questionnaire can be implemented via a web page withappropriate fields or the like for the company representative to inputtheir answer(s) to the individual question(s). The answers can then bereceived by, for example, a webserver.

FIG. 10 illustrates yet another embodiment of an additional exemplaryquestion for use in a questionnaire. The question of FIG. 10 isformatted to elicit a ranking of three qualities of importance toselecting a staffing partner. The factors are provided and the companyrepresentative can provide a ranking of first, second and third asappropriate. Again, the exemplary questionnaire can be implemented via aweb page with appropriate fields or the like for the companyrepresentative to input their answer(s) to the individual question(s).The answers can then be received by, for example, a webserver.

FIG. 11 illustrates an exemplary conclusion page to the questionnaire.The exemplary conclusion page illustrates that the questionnaire can beimplemented via a web page and the employer representative can concludethe questionnaire by selecting the submit button. At this time, all ofthe company representative's answers can be submitted and then received,for example, via a web server. Alternatively, the answers can besubmitted and received as soon as they are input by the employerrepresentative.

One embodiment of a method for a modeling staffing service level of acompany seeking one or more temporary or contingent employees isillustrated in FIG. 12 as a flow diagram. The method 1200 for modeling astaffing service level can start at 1210. At step 1220, responses to oneor more questionnaires can be received from one or more of company andcompany workforce representatives. The responses can be formatted in adata structure, such as utilizing extensible mark-up language, suitablefor parsing the responses to individual questionnaire questions. Thequestionnaire can include any one or more combinations of the exemplaryquestions from FIGS. 2-11.

Step 1220 can be repeated one or more times to receive responses to aquestionnaire from a plurality of company and company workforcerepresentatives. Step 1220A represents an example of receiving one ormore questionnaire responses from representatives of a company'sexecutive leadership team, such as presidents and officers. Step 1220Brepresents an of receiving one or more questionnaire responses fromrepresentatives of a company's hiring managers or supervisors. Step1220C represents an example of receiving one or more questionnaireresponses from representatives of a company's full-time workforce. Step1220D represents an example of receiving one or more questionnaireresponses from representatives of a company's contingent workforce. Step1220E represents an example of receiving one or more questionnaireresponses from any other type of company or company workforcerepresentative. Further, steps 1220A-E can be grouped by hierarchicallevel within the company. In addition to individual representativescores, each hierarchical group can have a questionnaire score byaveraging the scores from a particular hierarchical group. Furtherstill, all responses can be grouped together to create an overallcompany score. The system and method are not limited in the number ofcompany or permanent or temporary workforce representatives from whichquestionnaire responses can be received. Of all the responses received,certain questionnaire responses can be selected, which can include allof the responses received.

At step 1230, all questionnaire responses received are imported foranalysis with a statistical system or software, such as SPSS PredictiveAnalytics software. This process can utilize a webserver, outputting aformatted data structure from a database containing all questionnaireresponses, such as utilizing extensible mark-up language or acomma-separated values file, for utilization by the statistical systemor software.

Step 1240A is an example of where a hierarchical group's questionnairescore can be calculated. The calculation can include any appropriateformulae for providing one or more numerical values based on the answersto the questionnaire. As an example, the calculation can be thesummation of the numerical values selected by the company representativeor grouping of company representatives, where any non-numerical answersare correlated to a numerical value, for instance, on a scale of 1-10.Thus, in some instances, a hierarchical group's questionnaire score canbe based on the answers of a single representative. Also, if the scoreof more than one company representative is utilized, the scores can beaveraged by the number of company representative scores that isutilized.

Alternatively, the calculation can be provided via SPSS PredictiveAnalytics software. A correlation analysis may be performed to look fora relationship between the staffing service level factors. Amultivariate regression allowing for multiple dependent variables may becompleted using a variety of statistical techniques to identify certainservice level factors that uniquely and significantly contribute to theformula. Once the staffing service level factors for the model areselected, the individual regression coefficients may be determined usingthe least squared method. With the staffing service level factors forthe model, a factor analysis may be performed to identify groupings ofvariables or staffing service level factors and the associated factorloadings. A statistical staffing service level factor is constructedfrom groupings of variables with interdependent variability. Factorloadings are coefficients where the squared factor loadings show thepercent of variance in that indicator variable explained by the factor.The processor and memory may be configured to utilize the followingexemplary algorithms to calculate the score.

Correlation Analysis:

$s_{x}^{2} = {\frac{{\sum x^{2}} - \frac{\left( {\sum x} \right)^{2}}{n}}{n - 1} = \frac{{SS}(x)}{n - 1}}$

Mulitvariate Regression Model:

Y′i=b0+b1×li+b2×2i+ . . . bn×ni

Least Squares Model:

${f\left( {x_{i},\beta} \right)} = {\sum\limits_{j = 1}^{m}{\beta_{j}{\varphi_{j}\left( x_{i} \right)}}}$

where the coefficients, φ_(j), are functions of χ_(i).

Letting

$X_{ij} = {\frac{\partial{f\left( {x_{i},\beta} \right)}}{\partial\beta_{j}} = {{\varphi_{j}\left( x_{i} \right)}.}}$

where: {circumflex over (β)}=(X^(T)X)⁻¹X^(T)y.

A matrix based on N observations of responses to questionnaire questionscorrelated to observed staffing service levels from past engagements canbe used to identify determinative service level factors.

At step 1250, the representative questionnaire scores of steps 1240A-Bcan be compared to a statistical model that provides statistics ofservice levels, either rendered or expected, or both, of past renderedservices or past questionnaire scores. The statistical model can besegregated into a plurality of statistical model scores correlated todemographic data, such as average income, average education, and theunemployment rate, availability of employees based on the job/industry,total population in the geographic area of the client, how manycompanies in the area are similar to the client (e.g. classified byNAICS code). The demographic data can be based on geography, industriesor other categories. Thus, there can be a plurality of statistical modelscores correlated to industry, geographic region or other correlation.The aggregation of the statistical model scores can produce astatistical model average score for any correlation chosen. Further, thestatistical model average score can also be correlated to the title orlevel of the company representatives, or hierarchical groupings (e.g.,statistical model averages for CEOs, CFOs, etc.) such that differentstatistical model average scores can be calculated based on the title orlevel of the company representatives or hierarchical groupings thatanswered the questionnaire.

In comparing the hierarchical or overall company questionnaire scores ofsteps 1240A-B to the appropriate statistical model average score, thehierarchical or overall company questionnaire scores can be greater thanor less than the statistical model average score. The hierarchical oroverall company questionnaire score being greater than or less than thestatistical model average score can indicate staffing service leveltendency as determined in step 1260.

In step 1260, and based on comparing the hierarchical or overall companyquestionnaire scores to the appropriate statistical model average, astaffing service level tendency can be determined. The staffing servicelevel tendency can indicate the likelihood that a maximum staffingservice level by a provider of contingent workforce will at least meetthe expected staffing service level of the company given the company'scurrent circumstances. The tendency can also indicate if the level ofservices that will or are likely to be rendered will be below, at orabove the expected staffing service level. For instance, if thehierarchical or overall company questionnaire score is greater than thestatistical model average, the difference between the hierarchical oroverall company questionnaire score and the statistical model averagecan be used to determine a staffing service level tendency. Accordingly,the staffing service level tendency can be a percentage of likelihoodthat the maximum staffing services levels will be deficient, at orexceed expected staffing service levels. For instance, if thestatistical model average score for the chosen corresponding companyvariables is 75 and the hierarchical or overall company questionnairescore is 82, the difference between the two is 7. The difference of 7can be used to calculate a certain percentage likelihood that theexpected staffing service level will be met.

With the staffing service level tendency determined, the method can endat step 1260. Nevertheless, the hierarchical or overall companyquestionnaire score can also be saved in step 1265A shown as breakoutreference 1. Also, each representative score can be saved over time tocontinuously build a database of scores. Alternatively, only selectedrepresentative scores can be saved over time for inclusion with thedatabase of scores. With each new company or company workforcerepresentative questionnaire score, the model average can berecalculated in step 1265B. Again, there can be one or more statisticalmodel average scores based on, for example, demographic data, and aparticular statistical model average score can be recalculated when arepresentative score that is correlated to the particular demographicdata is calculated.

The method can also include comparing hierarchical or overall companyquestionnaire scores to scores of corresponding companies in step 1270.The comparison can include identifying corresponding companies with thesame score as the hierarchical or overall company questionnaire score,or scores within a standard deviation. For instance, scores within astandard deviation value of 1, 2, 3 or so on can be considered similar.The corresponding company scores can also be segregated into a pluralityof corresponding company scores correlated to demographic data, such asaverage income, average education, and the unemployment rate,availability of employees based on the job/industry, total population inthe geographic area of a respective client, how many companies in thearea are similar to the client (e.g. classified by NAICS code). Thedemographic data can be based on geography, industries or othercategories. Thus, there can be a plurality of corresponding companyscores correlated to industry, geographic region or other correlation.The term corresponding to describe this correlation. For example, acorresponding company score can be specific to a particular industrysuch that different industries can have different corresponding companyscores. Further, the corresponding company scores can also be correlatedto the title or level of the company representatives, or hierarchicalgroupings (e.g., statistical model averages for CEOs, CFOs, etc.) suchthat different corresponding company scores can be calculated based onthe title or level of the company representatives or hierarchicalgroupings that answered the questionnaire.

At step 1280, and based on comparing the hierarchical group or overallcompany questionnaire score to the scores of corresponding companies ofstep 1270, a maximum staffing service level can be determined. Themaximum staffing service level is based on actual staffing servicelevels rendered in the past and staffing metrics of the past. Thehierarchical group or overall company questionnaire score can becompared to corresponding company scores and the actual renderedstaffing service levels and staffing metrics for each correspondingcompany can be obtained. The maximum staffing service level is aplausible service level that will be rendered based on a correlation toactual past service levels with the same representative or hierarchicalscores or representative or hierarchical scores within a standarddeviation.

The maximum staffing service level can be determined by selecting anaverage maximum staffing service level from plausible staffing servicelevel averages associated with a range of corresponding company scores.For instance, the corresponding company scores can be provided in rangescorrelated to actual past staffing service level averages. Thus, themaximum staffing service levels can be correlated to actual staffingservice levels from past projects or engagements. As an example, thecorresponding company scores may indicate that the average maximumstaffing service level associated with scores in the range of scores of70-75 are correlated to an average maximum staffing service of 80. Therange can be smaller, such that each range is a single score or unit,and the range can be greater, such as range of 10 or 15 or even higher.

With the average maximum staffing service level determined, the methodcan end. However, the method can also provide the hierarchical group oroverall company questionnaire score along with staffing metrics datafrom an entity resource planning database of actual or rendered staffingservice levels associated with the hierarchical group or overall companyquestionnaire score. The combination of the hierarchical group oroverall company questionnaire score and the rendered staffing servicelevel associated with the hierarchical group or overall companyquestionnaire score can be input into a database of correspondingcompany scores. The average maximum staffing service level for the rangeof corresponding company scores can be updated over time in process1285A-B as the actual or rendered staffing service level data iscorrelated to the hierarchical group or overall company questionnairescores. The updated average maximum staffing service level data can beused for the next determination of a maximum staffing service levelaverage.

As indicated above, the system and method is arranged such that morethan one company representative score can be received and used. In thediscussion above, an executive level company representative'squestionnaire responses can be received at step 1220A. For instance, theexecutive level can be a CEO, CFO or generally any employee that cansign a contract for the employer to partner with a staffing company.

On the other hand, the method also includes receiving questionnaireresponses from a other company representatives, such as at step 1220B,where a non-executive level employee of the company, in this case ahiring manager or supervisor responds to the questionnaire. Generally,the hiring manager or supervisor would be an employee who is inimmediate contact with or will otherwise work directly with temporaryemployees or staff.

The method also includes receiving questionnaire responses from atemporary staff or contingent workforce representative at step 1220D,where the temporary staff or contingent workforce representative is nota full-time employee of the company but is a temporary employee orcontingent worker.

The questionnaire for the questionnaire responses received at step 1220Dcan be the same as, or different than the questionnaire for othercompany representatives discussed above. Nevertheless, the format of thequestions will be the same such that a score can be calculated in step1240A-B. Just like above, one or a combination of the questions from thequestionnaire can be selected for use in the calculation step 1240A-B.

In step 1240A-B, the contingent workforce representative questionnairescore can be calculated. Again, the calculation is the same calculationdiscussed above with respect to step 1240A-B.

Moving to step 1250, the contingent workforce representativequestionnaire score can be compared to a statistical model averagescore. The statistical model average score can be a single statisticalmodel average score for the method, or as discussed above, thestatistical model average score can be a statistical model average scorecorrelated to the type of temporary staff or contingent worker providingresponses, by demographics, skill set, length of temporary employment,or another correlation, to the questionnaire.

Again, based on a comparison of the contingent workforce representativequestionnaire score to a statistical model average score, a staffingservice level tendency can be determined in step 1250.

In instances where a plurality of hierarchical groups of company and/orcompany workforce representatives respond to the questionnaire, acomparison of the scores between the groups, as seen in step 1260, canalso be performed. This comparison can determine tendencies, orpercentage likelihoods, or variances between the staffing service levelexpectations of the various company hierarchical groups. Thesetendencies or variances can be used to trigger communications andpromote dialog concerning a contingent staffing engagement or caninfluence, or can be used to alter, determinative factors that canaffect the maximum staffing service level.

The questionnaire for the questionnaire responses received at steps1220A-E can be the same as, or different than the questionnaires for theother company or company workforce representatives. Nevertheless, theformat of the questions will be the same such that a score can becalculated in step 1240A-B. Just like above, one or a combination of thequestions from the questionnaire can be selected for use in thecalculation step 1240A-B.

In step 1280, an average maximum staffing service level can bedetermined by selecting from any combination or groupings onquestionnaire responses. Alternatively, a plurality of the determinedmaximum staffing service levels can themselves be averages to determinea combined average maximum staffing service level. The average maximumstaffing service level can provide a benchmark against which theexpected staffing service levels can be managed as discussed below.

The calculations and determinations can be utilized to increase servicelevels as shown in the method 1300. In step 1310, as also discussedabove with reference to method 1200, questionnaire responses can bereceived from one or more company representatives. An example would bethe partners of a law firm answering the questions as it relates totheir contingent workforce needs. Questionnaire responses could bereceived from a partner of the law firm as a company representative.Once questionnaire responses are received, one or more of thecalculations or determinations discussed with respect to FIG. 12 can beobtained.

At step 1320, after the questionnaire responses have been received fromstep 1310, the responses can be scored based on the statistical model asdiscussed above. The scores may then be used to determine the companyrepresentative's staffing services level expectations. Likewise, usingthe law firm example, all partners of the firm can provide questionnaireresponses in step 1310 and can be grouped by their hierarchical level.The hierarchical group questionnaire responses can be scored based onthe statistical model, determining the hierarchical groups expectedstaffing service level. Likewise again, this process can be repeated forall hierarchical groups at the firm, which can be used to create anoverall firm or company score. This overall company score can be used todetermine an overall company staffing service level expectation.

At step 1330, maximum staffing service levels can be determined. Asnoted previously, the maximum staffing service level can be the abilityof a provider of contingent workforce, or a staffing company, to meetcertain criteria. For instance, a company that engages a contingentworkforce provider can indicate that they seek a certain number ofemployees with a certain skill level for a project time period thatstarts on a certain day. Using the example above, the law firm couldrequest a contingent workforce provider to provide 10 staff attorneyswith contract drafting experience for a six month project that startswithin one month. The maximum staffing service level includes not justwhether the staff attorneys meet the initial requirements, but whetherthey remain on the project for the duration of the project. With themaximum staffing service levels determined in step 1330, differencesbetween company staffing service level expectations and the maximumstaffing service level achievable given the company's currentcircumstances can be determined. The differences may be great or small.

At step 1340, one or more factors that are determinative of thedifference between the expected staffing service level and the maximumstaffing service can be identified. The determinative factors can be anyone or more of the staffing service level factors. As non-limitingexamples, the determinative factors may be: whether if all of thetemporary positions are not filled, it has a significant impact on thecompany's ability to accomplish its goals; whether the internal hiringprocedures create barriers that influence staffing processes; whetherthe staffing provider is able to meet all of the company's staffingneeds; whether temporary employees are treated with the same respect asfull-time employees; and/or pay rates for temporary employees comparedto similar companies. The determinative factors can be identical to oneor more of the questions in the questionnaires. Alternatively, thedeterminative factors can be a factor or circumstance derived from oneor more staffing service level factors from the questionnaire. Thedeterminative factors may also be related to demographic data, such asdemographic data for a particular region. The determinative factors canbe identified by statistically analyzing the questionnaire responseswith respect to the data of corresponding companies. For example,corresponding company data may be staffing metrics of a company withvariables similar to the client with a similar maximum staffing servicelevel or similar staffing service level expectation. These metrics mayinclude observed average length of assignment or turnover reasons.Numerical analyses can be performed to identify one or more factors thatare outcome determinative.

At step 1350, and based on the identification of determinative factors,the maximum staffing service level can be increased to meet or exceedthe expected staffing service level. Additionally, the staffing servicelevel can increase relatively by the expected staffing service levelbeing influenced based on the identification of determinative factors.For instance, if a determinative factor for the maximum staffing servicelevel is the pay rate for temporary employees compared to correspondingcompanies, and the pay rate is identified as lacking in comparison tocorresponding companies, the pay rate can be increased. As anotherexample, a determinative factor for the maximum staffing service levelis whether temporary employees are treated with the same respect asfull-time employees, the contingent workforce provider and the clientcan cooperate to ensure that temporary employees are treated with thesame respect as full-time employees. Thus, in response to identifyingoutcome determinative factors, suggested changes can be provided by thecontingent workforce provider to the company. The suggested changes caninclude a report format listing the outcome determinative factor. Thereport can also include an indication of the impact of the outcomedeterminative factor on the maximum staffing service level. Addressingthese particular critical factors in these manners can ensure that themaximum staffing service level meets or exceeds the expected staffingservice level.

It is important to note that the methods described above may incorporateany of the functionality, devices, and/or features of the systemsdescribed above, or otherwise, and are not intended to be limited to thedescription or examples provided herein.

Referring now also to FIG. 14, at least a portion of the methodologiesand techniques described with respect to the exemplary embodiments canincorporate a machine, such as, but not limited to, computer system1400, or other computing device within which a set of instructions, whenexecuted, may cause the machine to perform any one or more of themethodologies or functions discussed above. The machine may beconfigured to facilitate various operations conducted by the system 100.For example, the machine may be configured to, but is not limited to,assist the system 100 by providing processing power to assist withprocessing loads experienced in the system 100, by providing storagecapacity for storing instructions or data traversing the system 100, orby assisting with any other operations conducted by or within the system100.

In some embodiments, the machine operates as a standalone device. Insome embodiments, the machine may be connected (e.g., using a network135) to and assist with operations performed by other machines, such as,but not limited to, the device 110, the server 140, the database 145, orany combination thereof. The machine may be connected with any componentin the system 100. In a networked deployment, the machine may operate inthe capacity of a server or a client user machine in server-client usernetwork environment, or as a peer machine in a peer-to-peer (ordistributed) network environment. The machine may comprise a servercomputer, a client user computer, a personal computer (PC), a tablet PC,a laptop computer, a desktop computer, a control system, a networkrouter, switch or bridge, or any machine capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that machine. Further, while a single machine is illustrated, theterm “machine” shall also be taken to include any collection of machinesthat individually or jointly execute a set (or multiple sets) ofinstructions to perform any one or more of the methodologies discussedherein.

The computer system 1400 may include a processor 1402 (e.g., a centralprocessing unit (CPU), a graphics processing unit (GPU, or both), a mainmemory 1404 and a static memory 1404, which communicate with each othervia a bus 1408. The computer system 1400 may further include a videodisplay unit 1410 (e.g., a liquid crystal display (LCD), a flat panel, asolid state display, or a cathode ray tube (CRT)). The computer system1400 may include an input device 1412 (e.g., a keyboard), a cursorcontrol device 1414 (e.g., a mouse), a disk drive unit 1416, a signalgeneration device 1418 (e.g., a speaker or remote control) and a networkinterface device 1420.

The disk drive unit 1416 may include a machine-readable medium 1422 onwhich is stored one or more sets of instructions 1424 (e.g., software)embodying any one or more of the methodologies or functions describedherein, including those methods illustrated above. The instructions 1424may also reside, completely or at least partially, within the mainmemory 1404, the static memory 1406, or within the processor 1402, or acombination thereof, during execution thereof by the computer system1400. The main memory 1404 and the processor 1402 also may constitutemachine-readable media.

Dedicated hardware implementations including, but not limited to,application specific integrated circuits, programmable logic arrays andother hardware devices can likewise be constructed to implement themethods described herein. Applications that may include the apparatusand systems of various embodiments broadly include a variety ofelectronic and computer systems. Some embodiments implement functions intwo or more specific interconnected hardware modules or devices withrelated control and data signals communicated between and through themodules, or as portions of an application-specific integrated circuit.Thus, the example system is applicable to software, firmware, andhardware implementations.

In accordance with various embodiments of the present disclosure, themethods described herein are intended for operation as software programsrunning on a computer processor. Furthermore, software implementationscan include, but not limited to, distributed processing orcomponent/object distributed processing, parallel processing, or virtualmachine processing can also be constructed to implement the methodsdescribed herein.

The present disclosure contemplates a machine readable medium 1422containing instructions 1424 so that a device connected to thecommunications network 135 can send or receive voice, video or data, andto communicate over the network 135 using the instructions. Theinstructions 1424 may further be transmitted or received over thenetwork 135 via the network interface device 1420.

While the machine-readable medium 1422 is shown in an example embodimentto be a single medium, the term “machine-readable medium” should betaken to include a single medium or multiple media (e.g., a centralizedor distributed database, and/or associated caches and servers) thatstore the one or more sets of instructions. The term “machine-readablemedium” shall also be taken to include any medium that is capable ofstoring, encoding or carrying a set of instructions for execution by themachine and that cause the machine to perform any one or more of themethodologies of the present disclosure.

The term “machine-readable medium” shall accordingly be taken toinclude, but not be limited to: solid-state memories such as a memorycard or other package that houses one or more read-only (non-volatile)memories, random access memories, or other re-writable (volatile)memories; magneto-optical or optical medium such as a disk or tape; orother self-contained information archive or set of archives isconsidered a distribution medium equivalent to a tangible storagemedium. In one embodiment, the machine readable storage medium may be amachine readable storage device. Accordingly, the disclosure isconsidered to include any one or more of a machine-readable medium or adistribution medium, as listed herein and including art-recognizedequivalents and successor media, in which the software implementationsherein are stored.

The illustrations of arrangements described herein are intended toprovide a general understanding of the structure of various embodiments,and they are not intended to serve as a complete description of all theelements and features of apparatus and systems that might make use ofthe structures described herein. Many other arrangements will beapparent to those of skill in the art upon reviewing the abovedescription. Other arrangements may be utilized and derived therefrom,such that structural and logical substitutions and changes may be madewithout departing from the scope of this disclosure. Figures are alsomerely representational and may not be drawn to scale. Certainproportions thereof may be exaggerated, while others may be minimized.Accordingly, the specification and drawings are to be regarded in anillustrative rather than a restrictive sense.

Thus, although specific arrangements have been illustrated and describedherein, it should be appreciated that any arrangement calculated toachieve the same purpose may be substituted for the specific arrangementshown. This disclosure is intended to cover any and all adaptations orvariations of various embodiments and arrangements of the invention.Combinations of the above arrangements, and other arrangements notspecifically described herein, will be apparent to those of skill in theart upon reviewing the above description. Therefore, it is intended thatthe disclosure not be limited to the particular arrangement(s) disclosedas the best mode contemplated for carrying out this invention, but thatthe invention will include all embodiments and arrangements fallingwithin the scope of the appended claims.

The foregoing is provided for purposes of illustrating, explaining, anddescribing embodiments of this invention. Modifications and adaptationsto these embodiments will be apparent to those skilled in the art andmay be made without departing from the scope or spirit of thisinvention. Upon reviewing the aforementioned embodiments, it would beevident to an artisan with ordinary skill in the art that saidembodiments can be modified, reduced, or enhanced without departing fromthe scope and spirit of the claims described below.

We claim:
 1. A system for modeling staffing service levels, comprising:a memory that stores instructions; and a processor that executes theinstructions to perform operations, the operations comprising: receivingquestionnaire responses to a questionnaire that elicits a perception ofstaffing service level factors of a plurality of representatives,wherein the questionnaire responses are provided by one of companyrepresentatives, company workforce representatives or a combinationthereof; selecting questionnaire responses of the representatives;determining an expected staffing service level; calculatingrepresentative questionnaire scores; comparing the representativequestionnaire scores to a statistical model; and determining a staffingservice level tendency based on comparing the representativequestionnaire scores to the statistical model, wherein the staffingservice level tendency indicates a likelihood that a maximum staffingservice level will at least meet the expected staffing service level. 2.The system of claim 1, wherein the company representative can beselected from the group consisting of an executive level employee, ahiring manager, and a supervisor; and wherein the company workforcerepresentative can be selected from the group consisting of a contingentemployee and a full-time employee.
 3. The system of claim 2, wherein theoperations further comprise: receiving questionnaire responses to thequestionnaire that elicits a perception of staffing service levelfactors of a hierarchical group of company representatives, wherein thequestionnaire responses are provided by a plurality of companyrepresentatives; selecting questionnaire responses of the hierarchicalgroup of company representatives; determining an expected staffingservice level for the hierarchical group; calculating a hierarchicalgroup questionnaire score; calculating an overall company questionnairescore; comparing the hierarchical group questionnaire score and overallcompany questionnaire score to a statistical model; and determining astaffing service level tendency based on comparing the hierarchicalgroup questionnaire score and overall company questionnaire score to astatistical model, wherein the staffing service level tendency indicatesa likelihood that a maximum staffing service level will at least meetthe expected staffing service level.
 4. The system of claim 3, whereinthe operations further comprise: comparing the overall companyquestionnaire score to corresponding company scores; and determining amaximum staffing service level based on comparing the overall companyquestionnaire score to corresponding company scores.
 5. The system ofclaim 4, wherein determining a maximum staffing service level furthercomprises selecting an average maximum staffing service level frompossible maximum staffing service level averages associated with a rangecorresponding company scores.
 6. The system of claim 5, wherein themaximum staffing service level is a staffing service level that willlikely be rendered given current circumstances of the company.
 7. Thesystem of claim 1, wherein the operations further comprise updating thestatistical model based on a recalculation utilizing the companyrepresentative questionnaire score.
 8. The system of claim 1, whereinthe operations further comprise updating the statistical model based ona recalculation utilizing the calculated hierarchical groupquestionnaire score and the calculated overall company questionnairescore.
 9. The system of claim 4, wherein the operations furthercomprise: updating the corresponding company scores with thequestionnaire responses received from the company representative; andrecalculating the statistical model based on the updated correspondingcompany scores.
 10. The system of claim 4, wherein the operationsfurther comprise: updating the corresponding company scores with thecalculated hierarchical group questionnaire score and the calculatedoverall company questionnaire score; and calculating possible maximumstaffing service level averages associated with a range of correspondingcompany scores.
 11. The system of claim 1, wherein the operationsfurther comprise: identifying outcome determinative factors from thestaffing service level factors; providing suggested changes, in responseto identifying outcome determinative factors, to increase the chancethat the maximum staffing service level will at least meet the expectedstaffing service level.
 12. A method for modeling staffing servicelevels, comprising: receiving questionnaire responses to thequestionnaire that elicits a perception of staffing service levelfactors of a hierarchical group of company representatives, wherein thequestionnaire responses are provided by a plurality of companyrepresentatives and wherein the company representative can be selectedfrom the group consisting of an executive level employee, a hiringmanager, and a supervisor; selecting questionnaire responses of thehierarchical group of company representatives; determining an expectedstaffing service level for the hierarchical group; calculating ahierarchical group questionnaire score; calculating an overall companyquestionnaire score; comparing the hierarchical group questionnairescore and overall company questionnaire score to a statistical model;and determining a staffing service level tendency based on comparing thehierarchical group questionnaire score and overall company questionnairescore to a statistical model, wherein the staffing service leveltendency indicates a likelihood that a maximum staffing service levelwill at least meet the expected staffing service level.
 13. The methodof claim 12, further comprising: comparing the overall companyquestionnaire score to corresponding company scores; and determining amaximum staffing service level based on comparing the overall companyquestionnaire score to corresponding company scores.
 14. The method ofclaim 12, further comprising: identifying outcome determinative factorsfrom the staffing service level factors; providing suggested changes, inresponse to identifying outcome determinative factors, to increase thechance that the maximum service level will at least meet the expectedstaffing service level.
 15. The method of claim 12, wherein calculatinga hierarchical group questionnaire score includes calculating aplurality of hierarchical group questionnaire scores for a plurality ofhierarchical groups; further comprising comparing the hierarchical groupquestionnaire scores; and determining a variance between thehierarchical group questionnaire scores.
 16. A computer-readable mediumcomprising instructions, which when executed by a processor, cause theprocessor to perform operations comprising: receiving questionnaireresponses to the questionnaire that elicits a perception of staffingservice level factors of a hierarchical group of companyrepresentatives, wherein the questionnaire responses are provided by aplurality of company representatives and wherein the companyrepresentative can be selected from the group consisting of an executivelevel employee, a hiring manager, and a supervisor; selectingquestionnaire responses of the hierarchical group of companyrepresentatives; determining an expected staffing service level for thehierarchical group; calculating a hierarchical group questionnairescore; calculating an overall company questionnaire score; comparing thehierarchical group questionnaire score and overall company questionnairescore to a statistical model; and determining a staffing service leveltendency based on comparing the hierarchical group questionnaire scoreand overall company questionnaire score to a statistical model, whereinthe staffing service level tendency indicates a likelihood that amaximum staffing service level will at least meet the expected staffingservice level.
 17. The computer-readable medium of claim 16, wherein theoperations further comprise: comparing the overall company questionnairescore to corresponding company scores; and determining a maximumstaffing service level based on comparing the overall companyquestionnaire score to corresponding company scores; wherein determininga maximum staffing service level further comprises selecting an averagemaximum staffing service level from possible maximum staffing servicelevel averages associated with a range corresponding company scores;wherein the maximum staffing service level is a staffing service levelthat will likely be rendered given the company's current circumstances.18. The computer-readable medium of claim 16, wherein the operationsfurther comprise: identifying outcome determinative factors from thestaffing service level factors; providing suggested changes, in responseto identifying outcome determinative factors, to increase the chancethat the maximum service level will at least meet the expected staffingservice level.